Copy number variation of individual cattle genomes using next-generation sequencing

USDA-ARS, ANRI, Bovine Functional Genomics Laboratory, Beltsville, Maryland 20705, USA.
Genome Research (Impact Factor: 14.63). 02/2012; 22(4):778-90. DOI: 10.1101/gr.133967.111
Source: PubMed


Copy number variations (CNVs) affect a wide range of phenotypic traits; however, CNVs in or near segmental duplication regions are often intractable. Using a read depth approach based on next-generation sequencing, we examined genome-wide copy number differences among five taurine (three Angus, one Holstein, and one Hereford) and one indicine (Nelore) cattle. Within mapped chromosomal sequence, we identified 1265 CNV regions comprising ~55.6-Mbp sequence--476 of which (~38%) have not previously been reported. We validated this sequence-based CNV call set with array comparative genomic hybridization (aCGH), quantitative PCR (qPCR), and fluorescent in situ hybridization (FISH), achieving a validation rate of 82% and a false positive rate of 8%. We further estimated absolute copy numbers for genomic segments and annotated genes in each individual. Surveys of the top 25 most variable genes revealed that the Nelore individual had the lowest copy numbers in 13 cases (~52%, χ(2) test; P-value <0.05). In contrast, genes related to pathogen- and parasite-resistance, such as CATHL4 and ULBP17, were highly duplicated in the Nelore individual relative to the taurine cattle, while genes involved in lipid transport and metabolism, including APOL3 and FABP2, were highly duplicated in the beef breeds. These CNV regions also harbor genes like BPIFA2A (BSP30A) and WC1, suggesting that some CNVs may be associated with breed-specific differences in adaptation, health, and production traits. By providing the first individualized cattle CNV and segmental duplication maps and genome-wide gene copy number estimates, we enable future CNV studies into highly duplicated regions in the cattle genome.

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    • "The development of SNP arrays allowed the identification of CNVs by high-throughput genotyping on different cattle breeds. CNV loci were identified in several indicine and taurine breeds, and CNV maps of the bovine genome, using SNPs, Next Generation Sequencing (NGS) and Comparative genome hybridization (CGH) arrays, were reported (Matukumalli et al., 2009; Bae et al., 2010; Fadista et al., 2010; Hou et al., 2012; Bickhart et al., 2012). In livestock , recent studies underlined the effects of the CNVs in intron 1 of the SOX5 gene causing the pea-comb phenotype in chickens (Wright et al., 2009), in the STX17 gene responsible for premature hair greying and susceptibility to melanoma in horses (Rosengren et al., 2008). "
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    ABSTRACT: The determination of copy number variation (CNV) is very important for the evaluation of genomic traits in several species because they are a major source for the genetic variation, influencing gene expression, phenotypic variation, adaptation and the development of diseases. The aim of this study was to obtain a CNV genome map using the Illumina Bovine SNP50 BeadChip data of 651 bulls of the Italian Brown Swiss breed. PennCNV and SVS7 (Golden Helix) software were used for the detection of the CNVs and Copy Number Variation Regions (CNVRs). A total of 5,099 and 1,289 CNVs were identified with PennCNV and SVS7 software, respectively. These were grouped at the population level into 1101 (220 losses, 774 gains, 107 complex) and 277 (185 losses, 56 gains and 36 complex) CNVR. Ten of the selected CNVR were experimentally validated with a qPCR experiment. The GO and pathway analyses were conducted and they identified genes (false discovery rate corrected) in the CNVR related to biological processes, cellular component, molecular function and metabolic pathways. Among those, we found the FCGR2B, PPARα, KATNAL1, DNAJC15, PTK2, TG, STAT family, NPM1, GATA2, LMF1, ECHS1 genes, already known in literature because of their association with various traits in cattle. Although there is variability in the CNVRs detection across methods and platforms, this study allowed the identification of CNVRs in Italian Brown Swiss, overlapping those already detected in other breeds and finding additional ones, thus producing new knowledge for association studies with traits of interest in cattle.
    Italian Journal of Animal Science 09/2015; 14:3900. DOI:10.4081/ijas.2015.3900 · 0.72 Impact Factor
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    • " 2010 ; Liu et al . 2010 ) , seven other studies were based on the BovineSNP genotyping array with 54 , 001 SNP probes ( Bae et al . 2010b ; Seroussi et al . 2010 ; Hou et al . 2011a , b , 2012b ; Cicconardi et al . 2013 ; Jiang et al . 2013 ) , and three studies were based on whole genome resequencing ( Stothard et al . 2011 ; Zhan et al . 2011 ; Bickhart et al . 2012 ) , respectively . Five studies reported no less than 300 CNVRs in different cattle breeds ."
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    ABSTRACT: In recent years, copy number variations (CNVs), which associate with complex traits such as disease and quantitative phenotypes, are increasingly recognized as an important and abundant source of genetic variation and phenotypic diversity. CNVs have been studied in several breeds of cattle with the goal of improving selection methods for commercial use; however, little is known about the extent to which CNVs contribute to genetic variation in Qinchuan cattle. The BovineHD Genotyping BeadChip array was used for analyzing the whole genomic CNVs of Qinchuan cattle breed; we discovered 367 unique CNV events from 6 Qinchuan cattle. Accounting for overlapping regions, a total of 365 autosomal copy number variation regions (CNVRs) (131 losses and 234 gains) were identified with an average number of 60.8 CNV events per individual, which covered 13.13 Mb of the cattle genomic sequence corresponding to 0.4 % of the whole cattle genome. The average and median sizes of CNVRs were 35.07 and 18.56 kb, respectively. The CNVRs map of Qinchuan cattle was first constructed based on the BovineHD Genotyping Beadchip array. Functional analysis indicated that most genes in CNVRs that were significantly enriched are involved in environmental stress. Comparison of CNVRs in ten published studies and the 365 CNVRs identified in our study overlapped 0.7–42.7 %. These findings are the first report of CNVs mapping in Qinchuan cattle and contribute to the greater understanding of CNV genetics in commercial cattle phenotypes.
    MGG Molecular & General Genetics 09/2014; 290(1). DOI:10.1007/s00438-014-0923-4 · 2.73 Impact Factor
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    • "It is notable that these genes are distributed merely in 1,820 CNVRs (58.1%) of all identified CNVRs, i.e., the remaining 41.9% CNVRs do not contain any annotated genes. The distribution of genes among CNVRs from the present studies is similar with those in other studies [4, 15, 25]. To test if the genes are enriched in these CNVRs, an empirical distribution of genes among CNVRs were constructed through 10,000 simulations. "
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    ABSTRACT: Background Copy number variations (CNVs) confer significant effects on genetic innovation and phenotypic variation. Previous CNV studies in swine seldom focused on in-depth characterization of global CNVs. Results Using whole-genome assembly comparison (WGAC) and whole-genome shotgun sequence detection (WSSD) approaches by next generation sequencing (NGS), we probed formation signatures of both segmental duplications (SDs) and individualized CNVs in an integrated fashion, building the finest resolution CNV and SD maps of pigs so far. We obtained copy number estimates of all protein-coding genes with copy number variation carried by individuals, and further confirmed two genes with high copy numbers in Meishan pigs through an enlarged population. We determined genome-wide CNV hotspots, which were significantly enriched in SD regions, suggesting evolution of CNV hotspots may be affected by ancestral SDs. Through systematically enrichment analyses based on simulations and bioinformatics analyses, we revealed CNV-related genes undergo a different selective constraint from those CNV-unrelated regions, and CNVs may be associated with or affect pig health and production performance under recent selection. Conclusions Our studies lay out one way for characterization of CNVs in the pig genome, provide insight into the pig genome variation and prompt CNV mechanisms studies when using pigs as biomedical models for human diseases. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-593) contains supplementary material, which is available to authorized users.
    BMC Genomics 07/2014; 15(1):593. DOI:10.1186/1471-2164-15-593 · 3.99 Impact Factor
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